classicvalues / kaladin

Machine learning tool aimed at automating cheat detection using insights data.

Kaladin

This machine learning tool is aimed at automating cheat detection on Lichess using insights (example).

It is built using CNNs on Keras/TensorFlow.

Setup

You will need:

• Linux OS (tested on Ubuntu 20.04 LTS)
• Docker
• MongoDB

Docker container setup for Tensorflow with CPU or GPU

Pre-requisites

Install Docker using your favorite package manager, or for example you can follow this guide.

Create custom image and container

Run $./docker.sh gpu|cpu [dev|prod] with the needed target, it will create/update the image and start the container. dev (default) will open bash, while prod will directly launch the queue manager: python3 queue_manager.py

Configuration

For the list of options and default values used by Kaladin, see src/.env.base. You can override these either by setting environmental variables or create a src/.env file.

Acknowledgments

The Kaladin repository was re-created when transitioning to open source to ensure that user data was not made public. Git history was expunged during that transition. A record of the commits prior to the transition can be found here:
Special thanks to:

• kraktus for your work on the queue manager, Docker config, error handling, lila integration, and integration testing.
• michael1241 for your domain expertise, design discussions, initial queue manager and mongo and deployment support.
• ornicar for your support, your mongo wizardry, and your lila integration work.
• the others around the globe who helped by validating the model output, generating ideas, and providing valuable feedback.